MCP Server Sample

# MCP Server Sample This repository contains an implementation of a Model Context Protocol (MCP) server for educational purposes. This code demonstrates how to build a functional MCP server that can integrate with various LLM clients.  # MCP Server Example This repository contains an implementation of a Model Context Protocol (MCP) server for educational purposes. This code demonstrates how to build a functional MCP server that can integrate with various LLM clients. References: - [Model Context Protocol - Anthropic](https://modelcontextprotocol.io/). - [MCP - Python](https://pypi.org/project/mcp/). ## What is MCP? MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications - it provides a standardized way to connect AI models to different data sources and tools. ### Key Benefits - A growing list of pre-built integrations that your LLM can directly plug into - Flexibility to switch between LLM providers and vendors - Best practices for securing your data within your infrastructure ## Architecture Overview MCP follows a client-server architecture where a host application can connect to multiple servers: - **MCP Hosts**: Programs like Claude Desktop, IDEs, or AI tools that want to access data through MCP - **MCP Clients**: Protocol clients that maintain 1:1 connections with servers - **MCP Servers**: Lightweight programs that expose specific capabilities through the standardized Model Context Protocol - **Data Sources**: Both local (files, databases) and remote services (APIs) that MCP servers can access ## Core MCP Concepts MCP servers can provide three main types of capabilities: - **Resources**: File-like data that can be read by clients (like API responses or file contents) - **Tools**: Functions that can be called by the LLM (with user approval) - **Prompts**: Pre-written templates that help users accomplish specific tasks ## System Requirements - Python 3.10 or higher - MCP SDK 1.2.0 or higher - `uv` package manager --- ### Installation Adding MCP to your python project We recommend using uv to manage your Python projects. If you haven't created a uv-managed project yet, create one: ``` uv init mcp-server-sample cd mcp-server-sample ``` Then add MCP to your project dependencies: ```console uv add "mcp[cli] ``` Alternatively, for projects using pip for dependencies: ```console pip install "mcp[cli]" ``` Running the standalone MCP development tools To run the mcp command with uv: ```console uv run mcp ``` ### Quickstart Let's create a simple MCP server that exposes a calculator tool and some data: ```python # server.py from mcp.server.fastmcp import FastMCP # Create an MCP server mcp = FastMCP("Demo") # Add an addition tool @mcp.tool() def add(a: int, b: int) -> int: """Add two numbers""" return a + b # Add a dynamic greeting resource @mcp.resource("greeting://{name}") def get_greeting(name: str) -> str: """Get a personalized greeting""" return f"Hello, {name}!" ``` You can install this server in Claude Desktop and interact with it right away by running: ```console mcp install server.py ``` Alternatively, you can test it with the MCP Inspector: ```console mcp dev server.py ``` Made with ❤️ by [Antonio Scapellato](https://scapellato.dev) #### Resources: - [Building Agents with Model Context Protocol - Full Workshop with Mahesh Murag of Anthropic](https://www.youtube.com/watch?v=kQmXtrmQ5Zg) #### License This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.